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This paper discusses the application of Dynamic Mode Decomposition (DMD) to the extraction of modal properties of linear mechanical systems, i.e., experimental modal analysis (EMA). First, theoretical background of the DMD is briefly…

Dynamical Systems · Mathematics 2026-03-17 Akira Saito , Tomohiro Kuno

We present a data-driven method for separating complex, multiscale systems into their constituent time-scale components using a recursive implementation of dynamic mode decomposition (DMD). Local linear models are built from windowed…

Systems and Control · Computer Science 2019-06-26 Daniel Dylewsky , Molei Tao , J. Nathan Kutz

A non-iterative waveform sensing approach is proposed toward (i) geometric reconstruction of penetrable fractures, and (ii) quantitative identification of their heterogeneous contact condition by seismic i.e. elastic waves. To this end, the…

Numerical Analysis · Mathematics 2018-01-11 Fatemeh Pourahmadian , Bojan B. Guzina , Houssem Haddar

Four different applications of spectral proper orthogonal decomposition (SPOD): low-rank reconstruction, denoising, frequency-time analysis, and prewhitening are demonstrated on large-eddy simulation data of a turbulent jet. SPOD-based…

Fluid Dynamics · Physics 2021-09-22 Akhil Nekkanti , Oliver T. Schmidt

Dynamic mode decomposition has emerged as a leading technique to identify spatiotemporal coherent structures from high-dimensional data, benefiting from a strong connection to nonlinear dynamical systems via the Koopman operator. In this…

Systems and Control · Computer Science 2017-12-01 Zhe Bai , Eurika Kaiser , Joshua L. Proctor , J. Nathan Kutz , Steven L. Brunton

Triadic interactions are the fundamental mechanism of energy transfer in fluid flows. This work introduces bispectral mode decomposition as a direct means of educing flow structures that are associated with triadic interactions from…

Fluid Dynamics · Physics 2021-01-20 Oliver T. Schmidt

The Dynamic Mode Decomposition (DMD) is a tool of trade in computational data driven analysis of fluid flows. More generally, it is a computational device for Koopman spectral analysis of nonlinear dynamical systems, with a plethora of…

Numerical Analysis · Mathematics 2017-08-10 Zlatko Drmač , Igor Mezić , Ryan Mohr

We present a new method for generating robust guesses for unstable periodic orbits (UPOs) by post-processing turbulent data using dynamic mode decomposition (DMD). The approach relies on the identification of near-neutral, repeated…

Fluid Dynamics · Physics 2020-02-19 Jacob Page , Rich R. Kerswell

Construction of reduced-order models (ROMs) for hyperbolic conservation laws is notoriously challenging mainly due to the translational property and nonlinearity of the governing equations. While the Lagrangian framework for ROM…

Numerical Analysis · Mathematics 2020-03-30 Hannah Lu , Daniel M. Tartakovsky

We develop a new method which extends Dynamic Mode Decomposition (DMD) to incorporate the effect of control to extract low-order models from high-dimensional, complex systems. DMD finds spatial-temporal coherent modes, connects local-linear…

Optimization and Control · Mathematics 2014-09-24 Joshua L. Proctor , Steven L. Brunton , J. Nathan Kutz

Understanding and controlling the dynamic interactions between fluid flows and solid materials and structures-a field known as fluid-structure interaction -is central not only to established disciplines such as aerospace and naval…

To understand the governing mechanisms of bio-inspired swimming has always been challenging due to intense interactions between the flexible bodies of natural aquatic species and water around them. In this paper, we employ advanced modal…

Fluid Dynamics · Physics 2020-05-19 Muhammad Saif Ullah Khalid , Junshi Wang , Imran Akhtar , Haibo Dong , Moubin Liu

We propose a new algorithm to compute a shifted proper orthogonal decomposition (sPOD) for systems dominated by multiple transport velocities. The sPOD is a recently proposed mode decomposition technique which overcomes the poor performance…

Numerical Analysis · Mathematics 2018-03-06 Philipp Schulze , Julius Reiss , Volker Mehrmann

Over the past few decades, there has been a rapid improvement in computational power as well as techniques to simulate the real world phenomenon which has enabled us to understand the physics and develop new systems which outperform the…

Computational Physics · Physics 2020-06-09 Sumant R Morab , Atul Sharma

High-speed stereo PIV-measurements have been performed in a turbulent boundary layer at Re$_{\theta}$ of 9800 in order to elucidate the coherent structures. Snapshot proper orthogonal decomposition (POD) and dynamic mode decomposition (DMD)…

Fluid Dynamics · Physics 2017-04-14 Naseem Ali , Murat Tutkun , Raúl Bayoán Cal

Dynamic Mode Decomposition (DMD) has received increasing research attention due to its capability to analyze and model complex dynamical systems. However, it faces challenges in computational efficiency, noise sensitivity, and difficulty…

Machine Learning · Computer Science 2025-02-20 Biqi Chen , Ying Wang

Based upon two overlapped, body-unfitted meshes, a type of unified-field monolithic fictitious domain-finite element method (UFMFD-FEM) is developed in this paper for moving interface problems of dynamic fluid-structure interactions (FSI)…

Numerical Analysis · Mathematics 2024-02-21 Cheng Wang , Pengtao Sun , Yumiao Zhang , Jinchao Xu , Yan Chen , Jiarui Han

In order to guarantee the safety of payload, crew, and structures, ships must exhibit good seakeeping, maneuverability, and structural-response performance, also when they operate in adverse weather conditions. In this context, the…

Dynamical Systems · Mathematics 2022-11-08 Andrea Serani , Paolo Dragone , Frederick Stern , Matteo Diez

Shape optimization is a challenging task in many engineering fields, since the numerical solutions of parametric system may be computationally expensive. This work presents a novel optimization procedure based on reduced order modeling,…

Numerical Analysis · Mathematics 2018-11-07 Nicola Demo , Marco Tezzele , Gianluca Gustin , Gianpiero Lavini , Gianluigi Rozza

Dynamic Mode Decomposition (DMD) is a data-driven decomposition technique extracting spatio-temporal patterns of time-dependent phenomena. In this paper, we perform a comprehensive theoretical analysis of various variants of DMD. We provide…

Numerical Analysis · Mathematics 2022-02-15 Tim Krake , Daniel Weiskopf , Bernhard Eberhardt
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